Data organization is how you organize the storage of your data. This can involve your filing strategy (folder / directory structure) as well as version control and management. How you organize (and later find) your data can have significant impacts on research efficiency and collaboration, and often has downstream affects on data documentation, storage, sharing, and preservation.
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Data documentation is how you describe your data — first for yourself and your research team, and later, more formally, to a broader community. Data documentation can be as a simple as a text document, or it can involve many interwoven applications and systems. Common data documentation methods include data dictionaries, lab notebooks, qualitative codebooks, etc. Data documentation also often involves using standardized naming and formatting conventions as well as data and metadata standards and ontologies.
Data documentation should capture the following elements:
Data documentation is closely related to data organization, as data organization structures are often recorded in data documentation.
Sharing data (with others or within a lab over time) is impossible without proper data documentation. "Metadata" is data about data. It's structured information that describes content and makes it easier to find or use. A metadata record can be embedded in data or stored separately. Any data file in any format can have metadata fields. In social science, this record is called the "codebook" or "data dictionary."
There are many metadata standards and which one is right for your data will depend on the type, scale, and discipline of your research project.
Some examples of metadata standards are:
For more examples, see the Research Data Alliance Metadata Directory.
If your field doesn't have a metadata standard (it may not be listed above) or if you just need a simpler system to keep track of data within your own lab, consider that there are three main types of metadata addressed by most standards:
Also consider this advice from the UK Data Archive [pdf]:
Good data documentation includes information on:
At the data-level, documentation may include: